Animal improvement has been achieved through selective breeding since the beginning of animal agriculture. In recent times, animal breeding employs a quantitative genetics approach, where improvement is based on evaluation of production records of progeny and relatives, e.g. records of milk production and carcass quality, followed by breeding pedigreed animals whose phenotypes are closest to a desired phenotype. Most improvement in dairy cattle, for example, is made through use of sire lines selected in this manner.
Marker-assisted selection using genetic markers that identify chromosomal regions containing genes (genetic loci) that affect quantitative traits (QTL) is an approach that is currently being developed by the animal breeding industry, e.g. for cattle traits. For example, a polymorphism in the somatotropin gene causing a change at amino acid position 126 provides a marker that can be correlated to the trait of superior milk production, but does not necessarily identify the polymorphism as the cause of the trait. The actual cause of the increased milk production may be due to some other closely linked (i.e. in close proximity) genetic factor or gene in the cattle genome, and not to the existence of the somatotropin polymorphism. Consequently, these statistics-based animal breeding methods are generally slow, expensive and inaccurate because the genes themselves underlying the traits of interest have not been identified, so selection does not achieve completely successful or predictable outcomes.
Further, complex gene action and interactions among genes serve to complicate objectives of traditional breeding programs. Selection based purely on phenotypic characteristics does not efficiently take into account such genetic variability, and is therefore not optimal.
For example, these traditional approaches are used for the purpose of selecting and breeding dairy cows capable of superior milk production. Although such programs have improved milk production, there are disadvantages because of the significant costs and time involved before the success of the program can be determined. For example, a traditional breeding program requires the breeding of many cows with a particular bull and subsequent analysis of the milk production of the female-progeny of these cows to determine whether the bull is of superior genetic value. A particularly successful breeding family of cattle is the Holstein line derived from the bull Carlin-M Ivanhoe Bell.
Female progeny must be raised, become pregnant, allowed to give birth and milked for a minimum length of time before milk production capabilities can be analyzed. Although this type of improvement program has improved milk production, there are disadvantages because of the significant costs and time involved before the success of the program can be determined. A breeding program relying on traditional techniques and selection criteria typically requires the investment of 4 or more years in a group of cattle before significant analysis of the program can be undertaken. It would, therefore, be advantageous if additional methods or criteria were available that were quicker and cheaper to determine whether a bull, heifer or cow should be included in a breeding program designed for superior milk production.
Boosting the level of growth hormones via introduction of additional hormones can improve cattle performance. An example is the use of bovine growth hormone or somatotropin. This has been made possible by the cloning and isolation of genes that express such proteins and then adding the resulting products of these commercially produced proteins to animals via feeds, injections, drugs, and the like. This method of boosting production of essential proteins however is inherently limited by the underlying genetics of the animal and because the effects are not heritable, does not offer anything in the way of selection of genetically superior animals for optimum genetic capabilities.
Furthermore, qualified administration of multiple injections of growth hormone keep costs high, and sick animals cannot be given growth hormone injections. There is also a concern that animals that are treated with growth hormone are more susceptible to mastitis. In addition, public acceptance of growth hormone is still uncertain. The results of bovine growth hormone injection include an increase in overall milk production, with no change in milk composition. This is a significant disadvantage because a dairy producer is paid on the basis of three milk characteristics, total volume of milk, total pounds of fat in the milk, and total pounds of protein in the milk, thus quality is as important as quantity. Producers may be paid more for protein than fat. Thus it can be seen that there is a continuing need for means of efficiently selecting and breeding cattle for improved milk production without concomitant decrease in milk composition, particularly protein content. In general, better methods of identifying animals with desirable predicted transmitting ability (PTA) for desirable phenotypes, such as high milk production and yield of protein and fat, are needed for long term benefits.
Microarrays are being developed for many research applications in animals, e.g. to study responses of genes to external stimuli. Microarray technology is revolutionizing biology by permitting the simultaneous analysis of transcript levels of thousands of genes in different physiological states of an organism, tissue or cell. Construction of microarrays is most efficient when information is utilized from annotated genome or EST sequencing projects. Evaluation of transcript levels using microarray technology has led to new insights into animal development, cancer, infectious diseases and aging. Microarrays have recently been produced for studying the functions of cattle genes and gene expression changes in different physiological states, although results to date have been quite limited.
In summary, a need exists in the art for a method of genetically evaluating animals such as ungulate (hoofed) mammals to enable breeders to more accurately select those animals which not only phenotypically express desirable traits, but those which express favorable underlying genetic criteria leading to the desired phenotypes. Therefore, it would be advantageous to find ways to more accurately predict quantitative traits from genomic information.